Research Article

Magnetic Resonance Materials in Physics, Biology and Medicine

, Volume 19, Issue 3, pp 134-143

First online:

Optimized diffusion gradient orientation schemes for corrupted clinical DTI data sets

  • J. DuboisAffiliated withService Hospitalier Frédéric Joliot, CEAIFR49Department of Radiology (CIBM), Geneva University Hospitals Email author 
  • , C. PouponAffiliated withService Hospitalier Frédéric Joliot, CEAIFR49
  • , F. LethimonnierAffiliated withService Hospitalier Frédéric Joliot, CEAIFR49
  • , D. Le BihanAffiliated withService Hospitalier Frédéric Joliot, CEAIFR49

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Abstract

Object:A method is proposed for generating schemes of diffusion gradient orientations which allow the diffusion tensor to be reconstructed from partial data sets in clinical DT-MRI, should the acquisition be corrupted or terminated before completion because of patient motion.

Materials and methods: A general energy-minimization electrostatic model was developed in which the interactions between orientations are weighted according to their temporal order during acquisition. In this report, two corruption scenarios were specifically considered for generating relatively uniform schemes of 18 and 60 orientations, with useful subsets of 6 and 15 orientations. The sets and subsets were compared to conventional sets through their energy, condition number and rotational invariance. Schemes of 18 orientations were tested on a volunteer.

Results: The optimized sets were similar to uniform sets in terms of energy, condition number and rotational invariance, whether the complete set or only a subset was considered. Diffusion maps obtained in vivo were close to those for uniform sets whatever the acquisition time was. This was not the case with conventional schemes, whose subset uniformity was insufficient.

Conclusion: With the proposed approach, sets of orientations responding to several corruption scenarios can be generated, which is potentially useful for imaging uncooperative patients or infants.

Keywords

Orientations Gradients DTI Motion Patient